Under climate change, back-to-back heat extremes threaten food production in Europe and the US, but most losses can be avoided by limiting global warming to 1.5 °C, according to a study led by ETH Zurich, Vrije Universiteit Amsterdam and the International Institute for Applied Systems Analysis (IIASA).
As the climate warms, extreme weather increasingly occurs in sequence. A new study in Environmental Research Letters, led by VU Amsterdam, ETH Zurich and the International Institute for Applied Systems Analysis (IIASA), together with co-authors from institutions across Europe and the United States, shows that such back-to-back heat events pose a serious threat to global food production.
The study shows that early-season heat can raise yield potential but leaves crops more vulnerable to subsequent heatwaves during the flowering period. Across maize, soybean, wheat, and barley in the US and Europe, spring heat leads to 5–55 percent larger losses from summer heat, compared to years with average spring conditions.
“Early heat can act like a double-edged sword", says environmental scientist Carmen B. Steinmann (ETH Zürich). “While it may boost yield potential at first, it leaves crops far more vulnerable when summer heat strikes", explains climate scientist Raed Hamed (VU Amsterdam).
Rising risks, avoidable losses
By the end of the century, sequential heat events could become up to ten times more frequent if emissions remain high. Accounting for this interaction increases projected yield losses by an additional 2–44 percent, offsetting potential benefits of warmer springs.
Limiting global warming to 1.5 °C reduces projected losses to just 1–6 percent. “This underlines how crucial rapid climate action to avoid societal impacts from increasingly complex climate risks," emphasizes Kai Kornhuber, climate researcher at IIASA.
Insights for resilient food systems
The study highlights the need to consider compounding climate extremes to strengthen food system resilience. By bridging detailed physiological insights from laboratory experiments with large-scale statistical analysis, it also provides guidance for climate adaptation planning.